56
2016 April
Foreign Financial Flows and
Terrorism – A Case Study of Pakistan
©Copyright is held by the author or authors of each Discussion Paper. Copenhagen Discussion Papers cannot be republished, reprinted, or reproduced in any format without the permission of the paper's author or authors.
Note: The views expressed in each paper are those of the author or authors of the paper. They do not represent the views of the Asia Research Centre or Copenhagen Business School.
Editor of the Copenhagen Discussion Papers: Associate Professor Michael Jakobsen
Asia Research Centre
Copenhagen Business School Porcelænshaven 24 DK-2000 Frederiksberg Denmark Tel.: (+45) 3815 3396 Email: [email protected] www.cbs.dk/arc
Foreign Financial Flows and Terrorism – A Case Study of
Pakistan
Amar Anwar
Shannon School of Business, Cape Breton University Sydney, Nova Scotia, Canada, B1P 6L2
Mazhar Mughal
Pau Business School, France Corresponding Author: Mazhar Mughal
Email: [email protected]
Abstract
This study examines the differential response of various international financial flows to the post 9/11 episode of terrorism in the context of a South Asian country. Using monthly data for the period from January 2003 to December 2014, we analyze the impact of terrorism in Pakistan on the inflows of foreign direct investment (FDI), portfolio investments, and migrant remittances. We find that FDI decreases substantially as a result of terrorist activity, whereas portfolio investments show little change. In contrast, migrant remittances show a significant increase. These differences are also evident in financial flows from major source regions and top sending countries. The results are robust to the use of alternative definitions and indicators of terrorism as well as the inclusion of various macroeconomic variables. These findings indicate that foreign private capital flees an economy suffering from terrorism whereas migrant remittances are the only financial flows that increase during difficult times.
Keywords: Terrorism; 9/11; FDI; Portfolio investment; Remittances; Developing countries; Pakistan.
1. Introduction
In the aftermath of the 9/11 attacks, literature has increasingly focused on the economic cost of terrorism. Terrorist activity is reported to have hit economic growth in both developing and developed countries and regions around the world (Abadie and Gardeazabal 2003; Eckstein and Tsiddon 2004; Crain and Crain 2006; Gaibulloev and Sandler 2008). This fall in growth of output occurs through multiple channels: Domestic consumption is increasingly diverted to security and defence spending leading to a larger government presence and greater budget deficits (Blomberg et al. 2004; Eckstein and Tsiddon 2004; Gupta et al. 2004) Investment in the economy drops due to higher production costs and growing interest rates; non defence-related production suffers, and the financial sector is crippled by rising transaction costs and scrutiny as well as documentation requirements (Eldor and Melnick 2004; Johnston and Nedelescu 2006).
Another channel through which terrorism can hurt an open economy is decrease in international financial flows to the terrorism-afflicted country. Financial flows, whether foreign direct investments (FDI), portfolio capital, or migrant remittances can all alter in the face of terrorism (Abadie and Gardeazabal 2008; Enders and Sandler 1996; Enders, Parise and Sandler 1992).
The direction and magnitude of the reaction of different foreign financial flows to terrorism may vary depending on the nature of those flows as well as the motives behind them. The degree to which financial flows respond to terrorism-induced economic shocks may determine the macroeconomic stability of a developing economy. This is of particular significance to capital-deficient developing countries that are heavily reliant on foreign financial flows, both for promoting growth and covering chronic current account deficits. During the early 2000s, international financial flows to developing countries grew substantially. At the same time, a new form of terrorist activity came to the fore, targeting mainly the United States and its allies. Given this background, this study examines the differential response of
various foreign financial inflows to post 9/11 terrorist activity. The analysis helps to distinguish between the risk profile of foreign investors and remitters in the face of terrorism.
The study uses monthly data on the three financial inflows (FDI, portfolio investments, and migrant remittances) as well as the terrorist activity which occurred in Pakistan between January 2003 and December 2014. The added value of this paper is three-fold:
Firstly, terrorism is a complex phenomenon resulting from the interaction of numerous social, economic and demographic factors which are area specific and thus cannot be adequately addressed in a cross-country setting. This study selects a developing country that is significant both for the amount of financial flows it receives, as well as the level of terrorist violence that has recently occurred in the country. In addition, comprehensive monthly data are employed for foreign financial flows and terrorism allowing a meaningful empirical investigation.
Secondly, the media coverage, and resulting risk perception of terrorist events, may vary from country to country; the impact of terrorism on the financial flows a country receives may consequently differ according to the countries and regions from which they originate. Therefore, the differential effects of the three flows are examined with respect to their provenance.
Thirdly, unlike most empirical studies on effects of terrorism on the economy which focus on a particular form of terrorism (e.g. transnational, domestic, business-related), this study considers the global effect of the terrorist activity. Along with the casualty count of civilian and security forces (which is taken as the principal terrorism indicator), the study evaluates the role of a number of significant terrorism incidents, such as bomb blasts and total fatalities, in shaping the volume of financial inflows.
2. Terrorism and Financial Flows: Theoretical Background and Literature Overview
According to Abadie and Gardeazabal (2008), capital mobility determines the equilibrium output level of an open economy. This occurs in two ways: directly through the destruction of physical assets, and more importantly, indirectly through a decrease in the marginal productivity of capital as a result of the terrorism shock. The latter leads potential foreign investors away to safer locations and thus hurts the economy's future output which results in low future growth even though the short term impact may not be substantial. This clear theoretical derivation has found mixed support in the empirical literature. For instance, Li (2006) finds no evidence that either anticipated or unanticipated terrorism has any direct effect on the location or volume of FDI. In their panel study on US FDI flows to a sample of 69 countries, Enders, Sachsida and Sandler (2006) find that, although transnational terrorist incidents have a statistically significant impact on US FDI in OECD countries, the relationship is not visible in non-OECD countries. Similarly, Blomberg and Mody (2005) report a qualified support for a negative impact of transnational terrorism on host country investments, finding that the relationship disappears if country fixed dummy variables are not employed. Power and Choi (2012) find that transnational terrorism that targets multinational investments in developing countries negatively affects FDI to those countries while non-business-related terrorism does not show a statistically significant impact.
Other empirical studies have found evidence for an unequivocally negative relationship between terrorism and FDI to the developing countries. Alomar and El-sakka (2011), for example report a negative impact of terrorism on FDI inflows to a sample of 136 developing countries. Likewise, Abadie and Gardeazabal (2008) examine the impact of terrorist violence on a cross-section of 186 countries and find a negative correlation between direct investments and terrorist violence. A one standard deviation increase in terrorist risk is reported to cause a five percent decrease in the affected country’s FDI to GDP ratio. Similarly, Lutz and Lutz (2006) suggest a substantial fall in the ability of Latin American economies to attract inward FDI due to terrorism.
The negative impact of terrorism on FDI flows may be due to several factors: Firstly, FDI is typically a long time investment and cannot easily be withdrawn without incurring losses. In other words, the investment itself becomes an exit-barrier for foreign investors (Rivoli & Salorio, 1996). Therefore, MNCs prefer to invest in larger and growing economies (Bandera & White, 1968; Lunn, 1980; Schneider & Frey, 1985), avoiding economies suffering from slow growth as a consequence of terrorism (Abadie and Gardeazabal 2003; Blomberg et al. 2004; Tavares 2004).
Secondly, terrorist incidents create an atmosphere of uncertainty (Abadie and Gardeazabal, 2008), and multinational corporations (MNCs) avoid investing in such countries. According to Abadie and Gardeazabal, FDI flows to the US fell from 15.8% of the Gross Fixed Capital Formation in 2000 to a mere 1.5% in 2003 in the aftermath of the 9/11 terrorist attacks. In contrast, US FDI outflows slightly increased in the same period.
Thirdly, terrorism can hurt productivity by raising transaction costs through increased security measures (Johnston and Nedelescu, 2005; Abadie and Gardeazabal,2008), leading the firm to lose its price competitiveness in the international markets (Moshirian,2006). Terrorist incidents trigger a generalized drop in asset prices, flight of capital and increase in operational costs for the firms (IMF, 2001; Johnston and Nedelescu, 2005).
Fourthly, governments of terror -stricken countries strengthen security measures which leads to higher budgetary allocations. Taxes need to be raised to finance these anti terrorism measures. Moreover, financial transactions face increased scrutiny as security agencies track potential terrorism financing. The monetary and business costs of these steps may deter foreign investors.
A possible reason for lack of consensus in empirical literature with regards to the significance and sign of terrorism’s impact on FDI may be the differences in the business environment and socioeconomic conditions of the investing countries.
Host countries with strong trade, cultural and historic ties with the home country may be well known to the investor who can therefore better evaluate the short and long-term risks involved in investments. However, home country media may give prominent coverage to terrorist activities in such countries which may lead to a heightened perception of threats in the investment destinations. The effect of terrorism in a country on its FDI inflows may therefore also depend on the extent its economic and security situation is known and understood in investing countries, and may subsequently vary from country to country.
The impact of terrorism on portfolio investments is likewise found to be negative in the empirical literature. Foreign portfolio investments (FPI) are more flexible than FDI and can be readily withdrawn from countries facing terrorist activity. Financial markets in developed country are more resilient to terrorism activity than those in their counterparts in developing countries (Arin et al. 2008; Chen and Siems, 2004).
Unlike the effects on FDI and FPI flows, the impact of terrorism on migrant remittances is ambiguous. Motives for remitting range from purely altruistic to purely self-interested. If the migrant maintains strong kinship ties with the country of origin and feels emotionally involved in the well being of relatives back home, he/she will tend to increase their financial assistance to help cover economic losses incurred due to terrorism. These altruistic remittances should therefore rise with terrorist violence. Carling, Erdal and Horst (2012), for instance, assert that ongoing conflict in the country of origin exerts an upward pressure on the migrants’ willingness to remit.
The positive remittance behaviour may also correspond to a co-insurance motive (Amuedo-Dorantes and Pozo 2006) as the migrant remitter helps the stay-behind members of the household in turn for their support in times of financial distress. On the other hand, a negative association between terrorism and remittance flows points to asset-accumulation and investment-related motives behind remitting
(Lukas and Stark 1985), as the migrant makes use of his/her knowledge of opportunities back home to invest in profitable ventures. This may particularly be the case if the migrant is permanently settled in the host country and considers the home country mainly as an investment destination.
These differences in motives may be evident in differential reactions to terrorism of the inflows from different countries.
Terrorism can also affect migration and subsequently have a positive impact on remittances through the size effect. Episodes of terrorist violence lead to outflows of migrants and refugees and create migrant communities abroad (Berdal 2005; Kaldor 2007; Omeje 2007). Dreher, Krieger and Meierrieks (2011) assessed the influence of terrorism on skilled migration for 152 countries over the 1976–2000 period and find robust evidence that terrorism increases skilled emigration, suggesting that terrorism affects the cost-benefit considerations of highly educated individuals in ways that make emigration more attractive. The resulting larger overseas migrant communities eventually lead to higher remittance inflows to the terrorism-afflicted country.
Following testable hypotheses can be identified from this discussion of the literature:
H1. FDI inflows fall as a result of terrorism.
This expectation is in line with Abadie and Gardeazabal (2008) capital flow theory as well as empirical evidence on the long-run impact of terrorism on FDI to developing countries (Alomar and El-sakka 2011; Lutz and Lutz 2006).
H2. The impact of terrorism on portfolio investments is negative.
During the first decade of this century stock markets of various developing countries including Pakistan rose sharply and subsequently attracted fresh capital from mature economies. High yield from stock markets in emerging countries
compensated for high terrorism-related variance. Nonetheless, sustained terrorist campaigns such as the one Pakistan is currently facing, harms the business environment and investments are prevented due to heightened risk perception. This can happen particularly if terrorist activity hits the country’s major production centers.
H3. Migrant remittances rise in response to terrorism.
Following Anwar and Mughal (2012) and Mughal and Anwar (2014), migrant remittances to Pakistan are expected to be predominantly altruistic in nature, and as a result may rise when the stay behind households face financial difficulty due to increased terrorist activity.
H4. The financial flows’ reaction to terrorism may vary with respect to their source regions and countries.
As described in the next section, Pakistan’s investment and remittance profile is diversified with substantial financial inflows received from three distinct regions. The list of source countries is likewise varied with source countries differing in historic and economic ties and geographical, demographic and economic profile. Financial flows may therefore behave differently based on their provenance.
3. Terrorism and Foreign Financial Flows to Pakistan: An overview
The inflows of FDI and portfolio investments received by Pakistan have fluctuated significantly. For instance, FDI flows to Pakistan jumped nine-fold between 2003 and 2007 to exceed US $5 billion only to fall again below $2 billion in 2011 (Fig. 1). FDI inflows often coincide with the country's business cycle, rising during the boom periods and falling during low-growth phases. A substantial share of FDI has been in the form of privatization receipts for previously state-owned corporations in the telecommunication and banking sectors. The United States, Europe and United Arab Emirates have historically been the major sources of FDI. The country’s FDI
portfolio is quite diverse with significant investments from countries in the EU, North America and Asia (Fig. 2).
Fig. 1. Net FDI to Pakistan (US $ million): 2003 – 2014
Source: Authors’ calculations based on SBP data (2015)
Fig. 2. Top FDI sources in Pakistan: 2003 - 2014
Source: Authors’ calculations based on SBP data (2015).
0 20 0 40 0 60 0 80 0 10 00 T o ta l NF DI i n ( US $ m illi on ) J a n 2 00 1 = 1 00 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1 2014m1 time 9
Foreign portfolio investments (FPI) to Pakistan have generally stayed low compared with other developing countries, and net inflows have surpassed $1 billion only once (in 2007). Net FPI inflows have been remarkably unstable. For instance the flows were negative for five of the thirteen years since 2001 (Fig. 3). The United States, UAE and UK account for much of the FPI investments the country receives (Fig. 4).
Fig. 3. Net foreign portfolio investment in Pakistan (US $ million): 2003 – 2014
Source: Authors’ calculations based on SBP data (2015).
-50 0 0 50 0 10 00 15 00 T o ta l NF P I in ( U S $ m ill io n) J a n 2 00 1 = 10 0 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1 2014m1 time 10
Fig. 4: Top sources of net foreign portfolio investment in Pakistan: 2003 -2014
Source: Authors’ calculations based on SBP data (2015).
In comparison, Pakistan received over US $12 billion migrant remittances in 2014 (Fig. 5), making it one of the top ten recipients of formal remittances in the world (State Bank of Pakistan 2013; World Bank 2011). Remittances comprise six percent of the country's GDP, surpassing the combined share of international capital inflows to Pakistan. The volume of formal remittances has risen sharply in the last decade, growing ten-fold between 2001 and 20141. The energy-rich states of the Persian Gulf are the main source of remittance flows to Pakistan along with North America and Europe (Fig. 6). Remittances to the country are considered a relatively stable source of foreign exchange (Mughal and Makhlouf, 2011), and are shown to be contra cyclical (Ahmed 2012).
1
For a recent account of the evolution and development impact of remittances to Pakistan, see for example Mughal (2013).
11
Fig. 5. Foreign remittances to Pakistan (US $ million): 2003 – 2014
Source: Authors’ calculations based on SBP data (2015).
Fig. 6. Top 5 remittance source countries: 2003-2014
Source: Authors’ calculations based on SBP data (2015).
20 0 40 0 60 0 80 0 10 00 12 00 T o ta l Re m it ta ne s i n ( US $ m illi on) J a n 20 01 = 1 00 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1 2014m1 time 12
Pakistan’s economy remains vulnerable to macroeconomic shocks arising within or outside the country's frontiers. Terrorism is one such shock that has hit the economy in the last decade. Although Pakistan has faced bouts of ethnic, separatist and sectarian violence in the past, anti-state militant activity surged spectacularly in the aftermath of 9/11 as the country joined the US-led campaign against Al-Qaida and the Taliban2. The number of deaths in terrorist attacks rose from 164 in 2003 to 3739 in 2012, before falling to 2314 in 2014 (Table 1). Most of the attacks have been carried out by the militant group Tehrik-e-Taliban Pakistan (TTP) followed by Baloch separatist groups and sectarian militants (Pakistan Security Report 2012). Target killings, bomb blasts, improvised explosive devices and rocket attacks have been the terrorists' main tactics.
Table 1: Terrorism in Pakistan (2003 -2014)
Year Number of Deaths Civilian Deaths Security Forces Deaths Terrorist' Deaths Number of Major Incidents Number of Bomb Blasts 2003 164 140 24 25 12 42 2004 619 435 184 244 23 137 2005 511 430 81 137 18 245 2006 933 608 325 538 42 300 2007 2119 1522 597 1479 157 677 2008 2809 2155 654 3906 243 598 2009 3315 2324 991 8389 364 499 2010 2265 1796 469 5170 348 463 2011 3503 2738 765 2800 269 635 2012 3739 3007 732 2472 255 648 2013 3677 3001 676 1702 345 375 2014 2314 1781 533 3182 401 375 Grand Total 25968 19937 6031 30044 2477 4994
Source: Authors’ calculations based on SATP data (2015).
2
For a brief background on the origins of terrorism in Pakistan, see Mehmood (2013).
13
Terrorism has exacted a heavy cost on the country, both in terms of lives and limbs as well as in material losses. According to Mehmood (2013), terrorism has cumulatively cost Pakistan 33.02 percent of its real national income during the 1973-2010 period, implying around one percent of lost real GDP per capita growth every year.
4. Data and Methodology 4.1. Data Description
Monthly time series for FDI, portfolio investments and migrant remittances are taken from Pakistan's central bank, the State Bank of Pakistan (SBP). All the series are in current US Dollars and are converted into constant US Dollars. FDI comprise investments by foreign corporations acquiring at least ten percent ownership of the local business. Investments involving less than ten percent foreign investor share are deemed portfolio investments. In addition to aggregate flows, both FDI and FPI are analyzed with respect to their source regions and countries. The regions considered are Asia, North America, and Western Europe. The list of countries for the constituent regions is given in Table A-5 in the appendix. United States, United Arab Emirates, United Kingdom, Netherlands and Switzerland were Pakistan’s top five FDI sources during the examined period, while the top five FPI senders were USA, UAE, UK, Singapore and Luxembourg. Remittances comprise the sum of workers’ remittances, compensation of employees, and migrants’ transfers. In addition to aggregate inflows, remittances from three major remitting regions and top five remitting countries are also considered. The regions included are Persian Gulf, North America and Europe3 4.
3
Unlike FDI and FPI, migrant remittances from Asia overwhelmingly originate in the Persian Gulf. Therefore, the latter can be taken as representing Asia. Similarly, FDI and FPI to Pakistan arriving from Europe originate almost exclusively in Western Europe. Therefore, the region is comparable to the Europe region taken as the source of remittance inflows.
4 The variable for Persian Gulf comprises observations for the six states of Gulf Cooperation Council (GCC), namely
Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates, while those for North America and Europe
14
Pakistan's top five sending countries during the period analyzed includes Saudi Arabia, United Arab Emirates, United States, United Kingdom and Kuwait. Together, these five account for the bulk of Pakistan’s remittance inflows.
Following Mughal and Anwar (2014), data on terrorism are taken from the South Asia Terrorism Portal (SATP). Studies on other countries and regions have often been based on data from Global Terrorism Database (GTD) maintained by the University of Maryland National Consortium for the Study of Terrorism and Response to Terrorism Center.
For South Asian countries however, including Pakistan, SATP provides more comprehensive data from 2003 onwards5.
Terrorism in this study pertains to both domestic and transnational attacks, although given the country context; attacks are overwhelmingly against domestic targets. Terrorism is defined as “an act or acts of criminal violence, or the sequence of actions leading to such an act or acts, which is/are intended to intimidate the public, coerce or unduly compel a government or public authority to perform or abstain from performing any act; or to destabilize or destroy the fundamental political, constitutional, economic or social structures of a country; or to overawe any public functionary or government agency” (SATP 2013).
We take the number of civilian and security -force fatalities in terrorist attacks as our main terrorism indicator. The reason for this choice is the following: during the period examined, the number of terrorism incidents in the country has been very high (as many as 47 terrorism incidents took place in a month involving three or more deaths). In such a situation, it is the intensity of attacks reflected in the number of deaths that is more significant than the incident count itself. As a
respectively consist of Canada and USA, and Belgium, Denmark, France, Germany, Greece, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, Switzerland and the United Kingdom.
5 Estimations are also carried out using the GTD database as a robustness measure. The results are similar to the study’s
main findings, and are not shown.
15
robustness check, the analysis is carried out using an alternative definition of the variable, including insurgent deaths in the death count. We also carry out the analysis using the number of incidents involving three or more deaths as well as the number of bomb blasts carried out during a month.
Monthly data for Pakistan's Consumer Price Index (CPI), interest rate and nominal exchange rate used in addition to the robustness checks are taken from the SBP. The terrorism series began from January 2003. As a result, the dataset contains a maximum of 144 observations for the January 2003 – December 2014 period. Summary statistics of the dataset are given in Table 2. An average of 180 people lost their lives every month during the examined period (excluding terrorists), while there was an average of 17 incidents involving three or more deaths per month.
Table 2: Summary Statistics
Number of Observations: 144
Variable Mean Std.
Dev. Min Max
Aggregate Net Foreign Direct Investment 165.84 168.06 -30.28 1010.68
Net Foreign Direct Investment from United States 33.29 33.97 -2.04 291.64
Net Foreign Direct Investment from UAE 23.53 70.55 -87.09 548.15
Net Foreign Direct Investment from UK 20.92 36.63 -32.78 318.80
Net Foreign Direct Investment from Netherlands 10.65 20.79 -30.15 186.38
Net Foreign Direct Investment from Switzerland 7.41 37.44 -105.68 363.05
Aggregate Net Foreign Portfolio Investment 36.41 162.10 -245.97 1562.22
Net Foreign Portfolio Investment from USA 13.88 44.50 -106.10 221.40
Net Foreign Portfolio Investment from UK 1.40 5.06 -15.01 32.42
Net Foreign Portfolio Investment from UAE 4.89 48.14 -98.99 505.52
Net Foreign Portfolio Investment from
Luxembourg 2.47 7.56 -13.90 58.71
Net Foreign Portfolio Investment from Singapore 0.54 10.41 -50.40 75.50
Aggregate Foreign Remittances 590.80 261.87 240.19 1263.13
Remittances from USA 121.00 26.49 74.63 203.73
Remittances from UK 63.93 42.49 19.21 182.19
Remittances from Saudi Arabia 140.84 94.90 31.71 372.17
Remittances from UAE 117.79 63.08 34.81 289.99
Remittances from Kuwait 28.22 10.34 10.84 56.57
Exchange Rate 76.36 16.65 57.33 107.51
Pakistan CPI (2010=100) 87.57 32.35 46.41 144.99
Death Count including terrorists 388.94 351.04 1.00 2024.00
Death Count 180.33 130.30 0.00 507.00
Civilian Death Count 138.45 107.26 0.00 432.00
Security Forces Death Count 41.88 34.43 0.00 157.00
Insurgents Death Count 208.64 264.00 0.00 1590.00
Number of Bomb Blasts 34.68 20.65 0.00 104.00
Major Incidents 17.20 13.02 0.00 47.00
Source: Authors’ calculations based on SATP and SBP data (2015).
4.2. Methodology
The time series included in the study are found to have a moving average component6. Moreover, terrorism is found to be exogenous with respect to the financial flows7. Given these characteristics of the dataset, the Autoregressive Integrated Moving Average (ARIMA) group of econometric techniques is considered pertinent for the analysis. The ARMAX model is chosen as the mainstay of the study. The general ARMAX (p, q) model in the context of our study can be expressed as:
FFi,t = α + β1 FFi,t-1 + .... + βp FFi,t-p + Ɣ0Tt+ Ɣ1Tt-1 + Ɛt - Ɵ1Ɛt-1 - .... - ƟqƐt-q
Where 'FF' represents the financial flow for the month t, ‘T’ is the terrorism indicator for the corresponding month and ℇ is the disturbance term. To apply ARMAX, the variables must be stationary, i.e. with constant mean and variance as well as constant auto- covariance over time.
We begin our empirical analysis by determining the level of stationarity of the aggregate, regional and country-wise financial flow series. Graphic evidence 6 The moving-average nature was tested using the Auto-Correlation (AC) and Partial Auto-Correlation (PAC) graphs
7
Endogeneity was determined using the Wu-Hausman specification test
17
suggests that all the series are non-stationary at levels, but turn stationary at first difference. The graphical evidence is confirmed by unit root tests (Table A-1in the Appendix). Appropriate lag structure is determined for the tests using the Akaike's Information Criterion (AIC) and the Schwarz Bayesian Information Criterion (SBIC) (Table A-1). The next step is to obtain the autocorrelation and partial-autocorrelation functions in order to determine the adequate lags for the aggregate, regional and top five country ARMAX models. The corresponding lags for the autocorrelation (AR) and moving average (MA) specifications obtained for the baseline models are given in Tables A-2. AIC and SBIC criteria are used to select the appropriate ARMAX models among suggested competing lag specifications. Most of the specifications thus selected are ARMAX (1,1,1). All the estimations are carried out using robust standard errors in order to control for potential heteroskedasticity in the models. Post-estimation tests are performed to check for autocorrelation in residuals (shown in Table A-3).
Granger causality test (Table A-4) shows that all the financial flows have one directional association with terrorism, running from terrorism to the financial inflow8.
5. Findings
Tables 3 to 5 present results for aggregate and country wise financial inflows. As shown in Tables 3 and 5, FDI and migrant remittances appear to react to the terrorism indicator (number of civilian and security-force fatalities) in a statistically significant manner, portfolio flows being insignificant (Table 4). The signs of association for FDI and remittances are opposite, though, and suggest the fact that the motives facing foreign investors and overseas Pakistani remitters are not the same. The coefficient of FDI's negative association with terrorism is a strong 0.05, implying a marginal effect of -0.38; one additional terrorism-related death is associated with a $0.38 million drop in FDI inflows. In comparison, remittances show a marginal rise of $0.09 million per additional death.
8
Li and Schaub (2004) also find no significant impact of FDI, FPI or migrant remittances on terrorism
18
Table 3. Aggregate and top 5 countries Net FDI inflows and terrorism (ARMAX)
These differential impacts are also evident in region-wise results9. FDI inflows from all the major source regions show strong negative association with terrorism. Similar to aggregate estimation, region-wise results for migrant remittances are all positive and significant. However, terrorism seems to have a small and marginally significant association with remittances from North America, which possibly points to a different socioeconomic profile of the North American Pakistani diaspora compared with the migrant communities located in the Persian Gulf and Europe.
9 The results explaining relationship between terrorism and region wise financial flows are not provided here and available
upon request.
ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1)
1 2 3 4 5 6
VARIABLES FDI_aggregate FDI_USA FDI_UAE FDI_UK FDI_Netherlands FDI_Switzerland
Terrorism -0.0489*** -0.0092*** -0.0072 -0.0047*** -0.0009 -0.0038 (0.0143) (0.0029) (0.0054) (0.0015) (0.0007) (0.0034) AR (1) 0.1171 0.1030 0.3831 0.0574 -0.0634*** 0.3604** (0.1322) (0.1315) (0.2753) (0.0411) (0.0228) (0.1585) MA(1) -0.8969*** -0.8491*** -1.0000*** -1.0000*** -1.0000*** -1.0000*** (0.0277) (0.0907) (0.0000) (0.0000) (0.0000) (0.0000) sigma 131.5268*** 25.6720*** 62.9387*** 35.2791*** 20.6321*** 34.0676*** (15.3618) (6.9932) (14.0652) (10.3336) (5.7386) (12.3909) Constant 9.5166*** 1.7223** 1.1598 0.9249*** 0.1528 0.6674 (3.6245) (0.8140) (1.1695) (0.3242) (0.1502) (0.7307) Observations 143 143 143 143 143 143
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
19
Table 4. Aggregate and top 5 countries Net FPI inflows and terrorism (ARMAX models)
Among the three major overseas communities, the North American Pakistani community is the wealthiest and the most educationally qualified (Mughal 2013; Oda 2009), and mostly comprises permanent migrants who may have a more investment-oriented perspective with respect to the home-country. The altruism-driven response to terrorism back home may thus be partially compensated by the community's investment-motivated reaction to organized violence.
The association between foreign portfolio investments and terrorism is negative for both the aggregate and country-wise estimations as expected (Table 4). However, most of the estimations are statistically insignificant. The predominantly weak significance of FPI’s association also suggests the presence of a factor which pulls portfolio investments in the opposite direction. Being more footloose than FDI, portfolio investments seek high yields in spite of high security risks as it is always possible to withdraw if the host economy is confronted with a shock. This has
ARIMA (1,1,1) AR(4) I(1) MA (1) ARIMA (1,1,1) ARIMA (1,1,1) AR(2) I(1) MA (1) ARIMA (1,1,1)
1 2 3 4 5 6
VARIABLES PFI_aggregate PFI_USA PFI_UAE PFI_UK PFI_Singapore PFI_Luxemburg
Terrorism -0.0005 -0.0040 -0.0001 -0.0025 -0.0004 0.0006 (0.0123) (0.0029) (0.0002) (0.0030) (0.0006) (0.0004) AR(1) -0.0561 -0.1471 -0.1080 0.4401** (0.0655) (0.1348) (0.1009) (0.2061) AR(2) -0.1769 (0.2173) AR(4) 0.3194*** (0.1227) MA(1) -0.8503*** -1.0000*** -1.0000*** -1.0000*** -1.0000*** -1.0000*** -0.1626 0 0 0 0 0 sigma 160.9802*** 41.4343*** 4.9637*** 47.4907*** 10.1919*** 6.2302*** (52.4135) (4.1890) (0.8146) (17.6100) (2.2168) (1.0298) Constant 1.3542 0.7682 0.0163 0.4798 0.0675 -0.0548 (2.4956) (0.6405) (0.0461) (0.6396) (0.1212) (0.0661) Observations 143 143 143 143 143 143
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
become increasingly possible thanks to financial globalization and advances in information and telecommunications technology.
Table 5. Aggregate and top 5 countries remittance inflows and terrorism (ARMAX models)
These findings corroborate the conclusions of a growing body of business literature that highlights the security risk-averse nature of foreign private capital. FDI usually denotes a long-term engagement with the host country and therefore requires trust in the prospects of the local economy. The higher security, insurance, transportation and production costs that result from terrorism-related uncertainty erode this trust and make the investors look for less risky avenues (Blomberg, Hess and Tan 2011; Frey, Luechinger and Stutzer 2007; Gaibulloev and Sandler 2011). Our findings are in contrast with those of Mehmood (2013) who fails to ascertain adverse effects of terrorism on FDI to Pakistan over the 1973-2010 period. In addition to different analytical tools employed, the two
ARIMA (1,1,1) ARIMA (1,1,1) AR(6) I(1) MA (1) ARIMA (1,1,1) ARIMA (1,1,1) AR(8) I(1) MA (1) 1 2 3 4 5 6
VARIABLES Remit_aggregate Remit_USA Remit_Saudi Arabia Remit_UAE Remit_UK Remit_Kuwait
Terrorism 0.0219* 0.0005 0.0083*** 0.0065 0.0062*** 0.0007 (0.0116) (0.0008) (0.0029) (0.0062) (0.0015) (0.0006) AR(1) -0.0752 0.2899*** -0.2289 0.2906 (0.4135) (0.0936) (0.6017) (0.2234) AR(6) -0.1997 (0.1272) AR(8) -0.2448*** (0.0938) MA(1) -0.7548* -1.0000*** -0.6901*** -0.3772 -0.9402*** -0.7365*** (0.4367) (0.0000) (0.0783) (0.6242) (0.1556) (0.1158) sigma 63.3339*** 15.0906*** 16.9522*** 17.9507*** 11.0626*** 3.3363*** (4.7655) (1.1291) (1.5028) (1.5343) (1.0390) (0.2625) Constant 1.4535 0.4019*** 0.5468 0.0708 -0.3148 0.0633 (1.8518) (0.1471) (0.4590) (0.9715) (0.2814) (0.1130) Observations 143 143 143 143 143 143
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
studies differ in the time scale and the period examined, suggesting that the long-term impact of terrorism on FDI may vary from its short-run effects.
In contrast to international private capital flows, migrant remittances to Pakistan chiefly correspond to altruistic motives. Migrants tend to remit more back home to help their family members or compatriots in general cope with terrorism-induced economic losses. This rise in remittances can also be due to increased migration of the more mobile sections of the population (especially that of skilled workers and professionals).
6. Robustness checks A. Post estimation tests
The estimated sets of ARMAX models need to be tested for the presence of white noise in the residuals. No autocorrelation of the estimated residuals is a prerequisite for good model fit. The models appear to be normally distributed. Augmented Dickey Fuller (ADF) and Phillip-Peron (PP) tests indicate no evidence of autocorrelation in residuals (Table A-3).
B. Estimations using alternate definitions of terrorism
We estimate the baseline aggregate models using several alternative definitions of terrorism. Table 6 shows the reaction of financial inflows to an incident count of the terrorist activity. A somewhat similar picture emerges. FDI from all source regions are significant and negative (country and regional level results are not shown). FDI from the developing countries (particularly those from Asia) show a strong drop in response to terrorism. Here too, portfolio investments retain their lack of significance on aggregate, region and country level. However, the behaviour of migrant remittance inflows changes. Even though the positive sign remains, many of the aggregate, regional and top five country estimations are no longer significant at the 10% significance level.
Table 6. Aggregate flows and major terrorism incidents (ARMAX models)
Table 7. Aggregate flows and bomb blasts count (ARMAX models)
ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1)
1 2 3
VARIABLES Aggregate Net FDI Aggregate Net FPI Aggregate Remittances
Major Incidents -0.4421*** 0.0621 0.2413*** (0.1214) (0.1175) (0.0227) AR(1) 0.1324 -0.0546 0.0954 (0.1334) (0.0634) (0.1141) MA(1) -0.9139*** -0.9119*** -1.0000*** (0.0311) (0.0542) (0.0000) Sigma 131.4714*** 160.8052*** 60.9281*** (15.1425) (51.9947) (4.6464) Constant 7.8688*** 0.1675 1.5585*** (2.9939) (1.7584) (0.3459) Observations 143 143 143
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
AR(2) I(1) MA (1) AR(7) I(1) MA (1) ARIMA(1,1,1)
1 2 3
VARIABLES Aggregate Net FDI Aggregate Net PFI Aggregate Remittances Bomb_Blasts -0.3075*** -0.1160** 0.1124 (0.1097) (0.0523) (0.0760) AR(1) -0.1176 (0.5430) AR(2) -0.1515* (0.0904) AR(7) -0.0642 (0.0473) MA(1) -0.8262*** -0.9181*** -0.7025 (0.0701) (0.0365) (0.5865) sigma 131.8475*** 159.9187*** 63.6083*** (16.8526) (52.8470) (4.6920) Constant 11.5315*** 5.6050** 1.4587 (4.3577) (2.6576) (2.8392) Observations 143 143 143 Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
We check the relationship between foreign financial flows and terrorism using another terrorism indicator: Bomb blasts are a major terrorism tactic in Pakistan. Results shown in Table 7 corroborate the findings of the incident count models. Although portfolio investments show significantly negative reaction to the number of bomb blasts carried out during a month, remittance receipts remain insignificant.
Finally, we estimate the terrorism – financial flows relationship employing another definition of terrorism by including the reported number of terrorists in the death count. Results given in Table 8 confirm the findings of our baseline models with all results maintaining their respective significance.
Table 8. Aggregate flows and terrorism – death count including terrorists (ARMAX models)
ARIMA (1,1,1) ARIMA (1,1,1) ARIMA (1,1,1)
1 1 1
VARIABLES Aggregate Net FDI Aggregate Net PFI Aggregate Remittances
Terrorism [death count including terrorists] -0.0209*** -0.0014 0.0083**
(0.0032) (0.0026) (0.0035) AR(1) 0.1176 -0.0553 -0.0724 (0.1277) (0.0633) (0.4086) MA(1) -1.0000*** -0.9115*** -0.7574* (0.0000) (0.0514) (0.4362) sigma 124.9648*** 160.9316*** 63.3309*** (14.8709) (52.4230) (4.7735) Constant 8.8198*** 1.8233 2.2083 (1.5998) (2.0604) (1.4076) Observations 143 143 143
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
C. Estimations using other macroeconomic drivers of foreign financial flows Financial inflows interact with various macroeconomic factors. Investors can modify their investment plans in view of exchange-rate variations. Similarly, if remittances are sent for investment in the local economy, depreciation may cause the remitter to delay or reconsider his/her investment decisions. A depreciating currency often signals deteriorating economic conditions. This may dissuade an investment-motivated migrant from remitting. However, if the migrant sends money to help the household maintain a certain standard of living; he/she will now need a lower amount of foreign currency to consume the same goods basket given the higher purchasing power of the foreign currency. Likewise, local market interest and inflation rates can affect the flow of foreign capital (Agarwal 1997; Tangjitprom 2012). The relationship between foreign financial flows and terrorism can be affected as a result. To account for this possibility, we estimate the aggregate models adding three macroeconomic variables, nominal exchange rate, Consumer Price Index (CPI) and interest rate. The results shown in Table 9 confirm our baseline results with all the models maintaining their signs, significance and respective coefficients. It should be noted here that, given that the data is monthly, other potentially important drivers of foreign flows such as growth in national output and domestic investment cannot be included in the aforementioned models.
Table 9. Aggregate flows and terrorism (ARMAX models including macroeconomic indicators)
7. Concluding Remarks
In the aftermath of the Sep 11 2001 terrorist attacks on the Twin Towers in New York, terrorism has become an everyday issue for many developing countries. At the same time, foreign financial flows have boomed as increasing amounts of private capital and migrant remittances have found home in many developing countries. In this study, we sought to analyze the response of foreign financial flows to terrorism. Using monthly data for the January 2003 - December 2014 period, we examined the relationship between terrorism and FDI, portfolio investments and migrant remittances to Pakistan. We found a substantial difference between the behaviour of these inflows in the face of terrorism. Private capital flows, particularly FDI, demonstrate a sizeable drop due to terrorist activity,
1 2 3
VARIABLES Aggregate Net FDI Aggregate Net FPI Aggregate Remittances Terrorism -0.0296*** -0.0188** 0.0051** (0.0065) (0.0080) (0.0026) Exchange Rate 0.2219 1.6523** -0.2858 (0.7637) (0.6682) (0.2316) CPI -0.0448 -0.7134** 0.1979* (0.3716) (0.2898) (0.1151) Money Market Rate 6.2079 4.6057 4.8033** (3.9303) (4.2013) (1.8743) AR(1) 0.0922 -0.0983 0.0721 (0.1273) (0.0788) (0.1158) MA(1) -1.0000*** -1.0000*** -1.0000*** (0.0001) (0.0000) (0.0000) sigma 123.3920*** 150.6814*** 60.1232*** (14.7520) (43.8705) (4.8976) Constant 0.2405 -54.0693** 8.5797 (23.8904) (22.0050) (7.1437) Observations 143 143 143 Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
whereas migrant remittances show an increase. Region- and country-wise flows indicate no specificities suggesting that investors and remitters from all the major source areas react in a similar fashion to bouts of terrorism.
In December 2014, a horrific terrorist attack on a school in North West Pakistan left 150 dead, most of them children. This widely mediatized attack has led to a strong response by the country’s security forces. Terrorist networks are being actively targeted, sleeper cells in urban areas are being destroyed, and the anti-terrorism judicial proceedings have been streamlined and accelerated. Part of the response to this challenge will ultimately have to be to offer economic incentives to the marginalized sections of the society. The findings of this study lead to certain economic policy implications in this regard: Foreign investments abstain from countries facing sustained terrorism activity. Governments of such countries should therefore not expect major FDI inflows while the security situation is not well under control. Instead of courting illusive foreign investors, a more productive strategy could be to provide a better business environment at home, allowing local businesses to create new jobs and expand production. Even though the terrorists may not target the businesses directly, it is the business companies that ultimately face the cost of insecurity. Better performance of existing businesses which in turn improve the local economic situation creates a disincentive for terrorists by raising the opportunity cost of terrorism. Another means of boosting the local economy can be to encourage migrant remittances by lowering remitting costs and facilitating more productive use of remittances. Given their relatively stable and countercyclical nature, remittances can be relied upon, in the short-term, to keep afloat a developing economy suffering from terrorism. Measures to tax these remittances may prove counterproductive.
References
Abadie, A. and Gardeazabal, J., 2003. The Economic Costs of Conflict: A Case Study of the
Basque Country. American Economic Review, 93 (1), 113–132.
Abadie, A. and Gardeazabal, J., 2005. Terrorism and the World Economy. University of the Basque
Country - Department of Foundations of Economic Analysis II. DFAEII Working Paper No. 2005-19. Available from: http://ideas.repec.org/p/ehu/dfaeii/200519.html.
Agarwal, R. N., 1997. Foreign Portfolio Investment in Some Developing Countries: A Study of
Determinants and Macroeconomic Impact. Indian Economic Review, (2), 217.
Ahmed, J., 2012. Cyclical Properties of Migrant’s Remittances to Pakistan: What the data tell us.
Economics Bulletin, 32 (4), 3266–3278.
Alomar, M. and El-Sakka, M. I. T., 2011. The Impact of Terrorism on the FDI Inflows to Less
Developed Countries: A Panel Study. European Journal of Economics, Finance &
Administrative Sciences, (28), 116–125.
Amuedo-Dorantes, C. and Pozo, S., 2006. Remittances as insurance: evidence from Mexican
immigrants. Journal of Population Economics, 19 (2), 227–254.
Anwar, A. I. and Mughal, M. Y., 2012. Motives to remit: some microeconomic evidence from
Pakistan. Economics Bulletin, 32 (1), 574–585.
Arin, K. P., Ciferri, D., and Spagnolo, N., 2008. The price of terror: The effects of terrorism on stock
market returns and volatility. Economics Letters, 101 (3), 164–167.
Bandera, V. N. and White, J. T., 1968. US direct investments and domestic markets in Europe, 21 (1), 117–233.
Berdal, M., 2005. Beyond greed and grievance. Review of International Studies, 31 (04), 687–698.
Blomberg, S. B. and Hess, G. D., 2006. How Much Does Violence Tax Trade? Review of
Economics and Statistics, 88 (4), 599–612.
Blomberg, S. B., Hess, G. D., and Orphanides, A., 2004. The macroeconomic consequences of
terrorism. Journal of Monetary Economics, 51 (5), 1007–1032.
Blomberg, S. B., Hess, G. D., and Tan, D. Y., 2011. Terrorism and the economics of trust. Journal
of Peace Research, 48 (3), 383–398.
Blomberg, S. B. and Mody, A., 2005. How severely does violence deter international investment?
Working paper series // Claremont Institute for Economic Policy Studies. No. 2005-01. Available from: http://www.econstor.eu/handle/10419/31451.
Carling, J., Erdal, M. B., and Horst, C., 2012. How does Conflict in Migrants’ Country of Origin Affect Remittance-Sending? Financial Priorities and Transnational Obligations Among
Somalis and Pakistanis in Norway. International Migration Review, 46 (2), 283–309.
Chen, A. H. and Siems, T. F., 2004. The effects of terrorism on global capital markets. European
Journal of Political Economy, 20 (2), 349–366.
Crain, N. V. and Crain, W. M., 2006. Terrorized economies. Public Choice, 128 (1-2), 317–349.
Dreher, A., Krieger, T., and Meierrieks, D., 2011. Hit and (they will) run: The impact of terrorism on
migration. Economics Letters, 113 (1), 42–46.
Eckstein, Z. and Tsiddon, D., 2004. Macroeconomic consequences of terror: theory and the case of
Israel. Journal of Monetary Economics, 51 (5), 971–1002.
Eldor, R. and Melnick, R., 2004. Financial markets and terrorism. European Journal of Political
Economy, 20 (2), 367–386.
Enders, W., Sachsida, A., and Sandler, T., 2006. The Impact of Transnational Terrorism on U.S.
Foreign Direct Investment. Political Research Quarterly, 59 (4), 517–531.
Enders, W. and Sandler, T., 1996. Terrorism and Foreign Direct Investment in Spain and Greece.
Kyklos, 49 (3), 331–352.
Enders, W., Sandler, T., and Parise, G. F., 1992. An Econometric Analysis of the Impact of
Terrorism on Tourism. Kyklos, 45 (4), 531–554.
Frey, B. S., Luechinger, S., and Stutzer, A., 2007. Calculating Tragedy: Assessing the Costs of
Terrorism. Journal of Economic Surveys, 21 (1), 1–24.
Gaibulloev, K. and Sandler, T., 2008. Growth Consequences of Terrorism in Western Europe.
Kyklos, 61 (3), 411–424.
Gaibulloev, K. and Sandler, T., 2011. The adverse effect of transnational and domestic terrorism on
growth in Africa. Journal of Peace Research, 48 (3), 355–371.
Gupta, S., Clements, B., Bhattacharya, R., and Chakravarti, S., 2004. Fiscal consequences of
armed conflict and terrorism in low- and middle-income countries. European Journal of
Political Economy, 20 (2), 403–421.
IMF, 2001. World Economic Outlook - The Global Economy after September 11.
IMF, 2011. Transactions with the Fund from May 01, 1984 to April 26, 2011.. Available from:
http://www.imf.org/external/np/fin/tad/extrans1.aspx?memberKey1=760&endDate=2011-04%2026&finposition_flag=YES.
IMF, 2013. International financial statistics. Available from: http://www.imf.org/en/Data.
Johnston, R. B. and Nedelescu, O. M., 2006. The impact of terrorism on financial markets. Journal
of Financial Crime, 13 (1), 7–25.
Kaldor, M., 2007. New & old wars. Stanford, Calif.: Stanford University Press.
Li, Q., 2006. Chapter 11 Political Violence and Foreign Direct Investment. Research in Global
Strategic Management, 12, 225–249.
Li, Q. and Schaub, D., 2004. Economic Globalization and Transnational Terrorism A Pooled
Time-Series Analysis. Journal of Conflict Resolution, 48 (2), 230–258.
Lucas, R. E. B. and Stark, O., 1985. Motivations to Remit: Evidence from Botswana. Journal of
Political Economy, 93 (5), 901–18.
Lunn, J., 1980. Determinants of U.S. direct investment in the E.E.C. European Economic Review,
13 (1), 93–101.
Lutz, B., 2006. International Terrorism in Latin America: Effects on Foreign Investment and
Tourism. Journal of Social, Political & Economic Studies, 31 (3). Available from:
http://opus.ipfw.edu/polsci_facpubs/49
Mirza, D. and Verdier, T., 2008. International trade, security and transnational terrorism: Theory
and a survey of empirics. Journal of Comparative Economics, 36 (2), 179–194.
Mughal, M. Y., 2013. Remittances as Development Strategy: Stepping Stones or Slippery Slope?
Journal of International Development, 25 (4), 583–595.
Mughal, M. Y. and Makhlouf, F., 2011. Volatility of Remittances to Pakistan: What do the Data Tell?
Economics Bulletin, 31 (1), 605–612.
Nitsch, V. and Schumacher, D., 2004. Terrorism and international trade: an empirical investigation.
European Journal of Political Economy, 20 (2), 423–433.
Oda, H., 2009. Pakistani migration to the United States : an economic perspective. Chiba : Inst. of
Developing Economies, Japan External Trade.
http://www.ide.go.jp/English/Publish/Download/Dp/pdf/196_oda.pdf.
Omeje, K., 2007. The diaspora and domestic insurgencies in Africa. African Sociological Review,
11 (2), 94–107.
Pakistan Institute for Peace Studies, 2012. Pakistan security report.. Available from:
http://san-pips.com/download.php?f=199.pdf
Powers, M. and Choi, S.-W., 2012. Does Transnational Terrorism Reduce Foreign Direct
Investment? Business-Related Versus non-Business-Related Terrorism. Journal of Peace
Research. Available from:
http://jpr.sagepub.com/content/early/2012/04/16/0022343312436768
Rivoli, P. and Salorio, E., 1996. Foreign Direct Investment and Investment under Uncertainty.
Journal of International Business Studies, 27 (2), 335–357.
SATP, 2015. South Asia Terrorism Portal.
Schneider, F. and Frey, B. S., 1985. Economic and political determinants of foreign direct
investment. World Development, 13 (2), 161–175.
State Bank of Pakistan., 2015. State Bank of Pakistan. Country-Wise Workers’ Remittances.
Available from: http://www.sbp.org.pk/ecodata/index2.asp
Sultan, M., 2013. Terrorism and the macroeconomy: evidence from Pakistan. Defence and Peace
Economics, (ahead-of-print), 1–26.
Tangjitprom, N., 2011. Macroeconomic Factors of Emerging Stock Market: The Evidence from
Thailand. Rochester, NY: Social Science Research Network. SSRN Scholarly Paper No. ID
1957697. Available from: http://papers.ssrn.com/abstract=1957697
Tavares, J., 2004. The open society assesses its enemies: shocks, disasters and terrorist attacks.
Journal of Monetary Economics, 51 (5), 1039–1070.
World Bank, 2011. Migration and Remittances Factbook 2011 | Data. Available from:
http://data.worldbank.org/data-catalog/migration-and-remittances
List of Appendices
Table A-1. Unit root tests for FDI , FPI and Remittances
Time Series
Number of lags As per AIC/SBIC criteria
ADF test statistics (τ)
PP test statistics (τ)
Critical Value (at 5 %)
Aggregate Net Foreign Direct Investment (D1) 3 -9.43 -20.02 -2.89
Net Foreign Direct Investment from United 2 -8.663 -20.686 -2.89
Net Foreign Direct Investment from UAE (D1) 4 -8.12 -16.002 -2.89
Net Foreign Direct Investment from UK (D1) 3 -8.882 -24.39 -2.89
Net Foreign Direct Investment from Netherlands 4 -7.823 -16.247 -2.89
Net Foreign Direct Investment from 4 -8.216 -28.081 -2.89
Aggregate Net Foreign Portfolio Investment 3 -7.966 -32.74 -2.89
Net Foreign Portfolio Investment from United 4 -6.989 -35.483 -2.89
Net Foreign Portfolio Investment from UAE (D1) 3 -9.002 -30.918 -2.89
Net Foreign Portfolio Investment from UK (D1) 3 -8.412 -26.068 -2.89
Net Foreign Portfolio Investment from 3 -8.52 -26.399 -2.89
Net Foreign Portfolio Investment from 2 -8.814 -17.912 -2.89
Aggregate Remittances (D1) 2 -8.306 -21.373 -2.89
Remittances from USA (D1) 2 -8.146 -17.979 -2.89
Remittances from Saudi Arabia (D1) 1 -8.551 -16.712 -2.89
Remittances from UAE (D1) 1 -9.68 -15.851 -2.89
Remittances from UK (D1) 3 -7.217 -17.151 -2.89
Remittances from Kuwait (D1) 1 -9.645 -17.104 -2.89
Note: D1 = stationary at first difference
Table A-2. Lags Selection for FDI and FPI ARMAX Models Time Series Number of lags for autoregressive term ‘ p’
Number of lags for moving average
term ‘ q’
Aggregate Net Foreign Direct Investment (D1) 1, 2, 4, 5, 8 1 , 6
Net Foreign Direct Investment from United States (D1) 1, 2 1, 2, 3, 6
Net Foreign Direct Investment from UAE (D1) 1, 2, 4, 8 1, 2
Net Foreign Direct Investment from UK (D1) 1, 2, 3, 5 1
Net Foreign Direct Investment from Netherlands (D1) 1, 2, 4 1, 2
Net Foreign Direct Investment from Switzerland (D1) 1, 2, 3, 4, 10, 11 1
Aggregate Net Foreign Portfolio Investment (D1) 1, 2, 3, 7 1, 4, 5
Net Foreign Portfolio Investment from United States (D1) 1,3, 4 1, 2, 3, 4
Net Foreign Portfolio Investment from UAE (D1) 1, 2, 3, 6, 8 1
Net Foreign Portfolio Investment from UK (D1) 1, 2, 3, 5, 7 1
Net Foreign Portfolio Investment from Singapore (D1) 1, 2, 3 1, 2, 4, 5
Net Foreign Portfolio Investment from Luxembourg (D1) 1, 2, 6, 7 1
Aggregate Remittances (D1) 1 1
Remittances from USA (D1) 1, 8, 12 1
Remittances from Saudi Arabia (D1) 1, 6, 8 1, 6, 8
Remittances from UAE (D1) 1, 5 1
Remittances from UK (D1) 1, 3 1
Remittances from Kuwait (D1) 1, 7 1
Note: D1 = stationary at first difference
Table A-3. ADF and PP tests for Residuals Time Series ADF test statistics (τ) on PP test statistics (τ) on Residuals Critical Value (at 5 %)
Aggregate Net Foreign Direct Investment -11.018 -11.017 -2.89
Net Foreign Direct Investment from United States -11.026 -11.045 -2.89
Net Foreign Direct Investment from UAE -10.473 -10.464 -2.89
Net Foreign Direct Investment from UK -10.521 -10.523 -2.89
Net Foreign Direct Investment from Netherlands -10.448 -10.435 -2.89
Net Foreign Direct Investment from Switzerland -11.21 -11.257 -2.89
Aggregate Net Foreign Portfolio Investment (D1) -11.251 -11.253 -2.89
Net Foreign Portfolio Investment from United States -10.743 -10.738 -2.89
Net Foreign Portfolio Investment from UAE (D1) -11.078 -11.099 -2.89
Net Foreign Portfolio Investment from UK (D1) -11.127 -11.129 -2.89
Net Foreign Portfolio Investment from Singapore (D1) -11.113 -11.113 -2.89
Net Foreign Portfolio Investment from Luxembourg -11.244 -11.249 -2.89
Aggregate Remittances (D1) -11.190 -11.211 -2.89
Remittances from USA (D1) -11.311 -11.306 -2.89
Remittances from Saudi Arabia (D1) -10.488 -10.505 -2.89
Remittances from UAE (D1) -11.369 -11.348 -2.89
Remittances from UK (D1) -10.316 -10.338 -2.89
Remittances from Kuwait (D1) -11.007 -11.090 -2.89
Table A-4. Test for Granger causality (Aggregate models)
Model F-Statistics Prob > F
Aggregate Net Foreign Direct Investment F( 4, 113) = 1.49 Prob > F = 0.2097
Aggregate Net Foreign Portfolio Investment F( 4, 113) = 2.35 Prob > F = 0.0887
Aggregate Remittances F( 4, 112) = 1.52 Prob > F = 0.2004
Table A-5. List of source countries and regions for FDI and FPI
Developed countries: Luxembourg, Denmark, France, Germany, Netherlands, Sweden, U.K, Norway, Switzerland, Canada, U.S.A, Australia, Japan
Developing countries : Libya, Egypt, Mauritius, South Africa, Oman, Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, Turkey, U.A.E, Bangladesh, China, Hong Kong, Malaysia, Singapore, India, Korea (South), Caribbean Islands, Cayman Island, Bahamas
Asia: Oman, Iran, Kuwait, Bahrain, Qatar, Saudi Arabia, Turkey, U.A.E, Bangladesh, China, Hong Kong, Malaysia, Singapore, India, Korea (South)
Western Europe: Luxembourg, Denmark, France, Germany, Netherlands, Sweden, U.K, Norway, Switzerland
North America: Canada, U.S.A
Africa: Libya, Egypt, Mauritius, South Africa
COPENHAGEN DISCUSSION PAPERS 2005:
2005-1 May: Can–Seng Ooi - Orientalists Imaginations and Touristification of Museums: Experiences from Singapore
2005-2 June: Verner Worm, Xiaojun Xu, and Jai B. P. Sinha - Moderating Effects of Culture in Transfer of Knowledge: A Case of Danish Multinationals and their Subsidiaries in P. R. China and India
2005-3 June: Peter Wad - Global Challenges and Local Responses: Trade Unions in the Korean and Malaysian Auto Industries
2005-4 November: Lenore Lyons - Making Citizen Babies for Papa: Feminist Responses to Reproductive Policy in Singapore
2006:
2006-5 April: Juliette Koning -On Being “Chinese Overseas”: the Case of Chinese Indonesian Entrepreneurs
2006-6 April: Mads Holst Jensen - Serve the People! Corporate Social Responsibility (CSR) in China
2006-7 April: Edmund Terence Gomez - Malaysian Investments in China: Transnationalism and the ‘Chineseness’ of Enterprise Development
2006-8 April: Kate Hannan - China’s Trade Relations with the US and the EU WTO Membership, Free Markets (?), Agricultural Subsidies and Clothing, Textile and Footwear Quotas
2006-9 May: Can- Seng Ooi - Tales From Two Countries: The Place Branding of Denmark and Singapore
2006-10 May: Gordon C. K. Cheung - Identity: In Searching the Meaning of Chineseness in Greater China
2006-11 May: Heidi Dahles - ‘Chineseness’ as a Competitive Disadvantage, Singapore Chinese business strategies after failing in China
2006-12 June: Émile Kok- Kheng Yeoh - Development Policy, Demographic Diversity and Interregional Disparities in China
2006-13 June: Johannes Dragsbaek Schmidt - China’s "soft power" re-emergence in Southeast Asia
2006-14 September: Michael Jacobsen - Beyond Chinese Capitalism:
Re-Conceptualising Notions of Chinese-ness in a Southeast Asian Business cum Societal Context
2006-15 October: Ng Beoy Kui - The Economic Rise of China: Its Threats and Opportunities from the Perspective of Southeast Asia
2007:
2007-16 February: Michael Jacobsen - Navigating between Disaggregating Nation States and Entrenching Processes of Globalisation: Reconceptualising the Chinese Diaspora in Southeast Asia
2007-17 April: Émile Kok-Kheng Yeoh, Shuat-Mei Ooi - China-ASEAN Free Trade Area: Implications for Sino-Malaysian Economic Relations
2007-18 May: John Ravenhill, Yang Jiang - China’s Move to Preferential Trading:An Extension of Chinese Network Power?
2007-19 May: Peter J. Peverelli - Portof Rotterdam in Chinese Eyes
2007-20 June: Chengxin Pan - What is Chinese about Chinese Business? Implications for U.S. Responses to China’s Rise
2007-21 September: Charles S. Costello III - The Irony of the Crane: Labour Issues in the Construction Industry in the New China
2007-22 October: Evelyn Devadason - Malaysia-China Network Trade: A Note on Product Upgrading
2007-23 October: LooSee Beh - Administrative Reform: Issues of Ethics and Governance in Malaysia and China
2007-24 November: Zhao Hong - China- U.S. Oil Rivalry in Africa
2008:
2008-25 January: Émile Kok-Kheng Yeoh - Ethnoregional Disparities, Fiscal Decentralization and Political Transition: The case of China
2008-26 February: Ng Beoy Kui - The Economic Emergence of China: Strategic Policy Implications for Southeast Asia
2009:
2009-28 July: Xin Li, Verner Worm - Building China’s soft power for a peaceful rise 2009-29 July: Xin Li, Kjeld Erik Brødsgaard, Michael Jacobsen - Redefining Beijing Consensus: Ten general principles
2009-30 August: Michael Jacobsen - Frozen Identities. Inter-Ethnic Relations and Economic Development in Penang, Malaysia
2010:
2010-31 January: David Shambaugh – Reforming China’s Diplomacy
2010-32 March: Koen Rutten - Social Welfare in China: The role of equity in the transition from egalitarianism to capitalism
2010-33 March: Khoo Cheok Sin - The Success Stories of Malaysian SMEs in Promoting and Penetrating Global Markets through Business Competitiveness Strategies
2010-34 October: Rasmus Gjedssø and Steffen Møller – The Soft Power of American Missionary Universities in China and of their Legacies: Yenching University, St. John’s University and Yale in China
2010-35 November: Michael Jacobsen - Interdependency versus Notions of Decoupling in a Globalising World: Assessing the Impact of Global Economics on Industrial
Developments and Inter-Ethnic Relations in Penang, Malaysia
2010-36 November:Kjeld Erik Brødsgaard – Chinese-Danish Relations: The Collapse of a special Relationship
2011:
2011-37 April: Masatoshi Fujiwara – Innovation by Defining Failures under Environmental and Competitive Pressures: A Case Study of the Laundry Detergent Market in Japan 2011-38 November: Kjeld Erik Brødsgaard - Western Transitology and Chinese Reality: Some Preliminary Thoughts
2012:
2012-39 December: Kjeld Erik Brødsgaard - Murder, Sex, Corruption: Will China Continue to Hold Together?
2013:
2013-40 January: Sudipta Bhattacharyya, Mathew Abraham and Anthony P. D’Costa - Political Economy of Agrarian Crisis and Slow Industrialization in India
2013-41 February: Yangfeng Cao, Kai Zhang and Wenhao Luo - What are the Sources of Leader Charisma? An Inductive Study from China
2013-42 April: Yangfeng Cao, Peter Ping Li, Peter Skat-Rørdam - Entrepreneurial
Aspiration and Flexibility of Small and Medium-Sized Firms: How Headquarters Facilitate Business Model Innovation at the Subsidiary Level
2013-43 October: Zhiqian YU, Ning ZHU, Yuan ZHENG - Efficiency of Public Educational Expenditure in China
2013-44: November: Yangfeng Cao - Initiative-taking, Improvisational Capability, and Business Model Innovation in Emerging Markets
2014:
2014-45 January: Michael Jakobsen - International Business Studies and the Imperative of Context. Exploring the ‘Black Whole’ in Institutional Theory
2014-46 February: Xin Li - The hidden secrets of the Yin-Yang symbol 2015:
2015-47 March: Aradhna Aggarwal and Takahiro Sato – Identifying High Growth Firms in India: An Alternative Approach
2015-48 May: Michael Jakobsen - Exploring Key External and Internal Factors Affecting State Performance in Southeast Asia
2015-49 May: Xin Li, Peihong Xie and Verner Worm - Solutions to Organizational Paradox: A Philosophical Perspective
2015-50 June: Ari Kokko - Imbalances between the European Union and China
2015-51 August: Chin Yee Whah - Changes of Ownership and Identities of Malaysian Banks: Ethnicity, State and Globalization
2015-52 November: Abdul Rahman Embong - State, Development and Inequality in Selected ASEAN Countries: Internal and External Pressures and State Responses 2015-53 November: Verner Worm, Xin Li, Michael Jakobsen and Peihong Xie - Culture studies in the field of international business research: A tale of two paradigms
2016:
2016-54 April: Vinish Kathuria - Does Environmental Governance matter for FDI? – Testing for Pollution Haven Hypothesis for Indian States
2016-55 April: Shruti Sharma - Does Plant Size Matter? Differential Effects of FDI on Wages and Employment in Indian Manufacturing
2016-56 April: Amar Anwar and Mazhar Mughal - Foreign Financial Flows and Terrorism – A Case Study of Pakistan
